Digital images may become noisy during acquisition or transmission, resulting in the reduced quality of the digital images.
Reducing the noise, or denoising, of the digital image still remains a challenge, because noise reduction introduces artifacts and causes blurring of digital images.
There are various existing denoising techniques, each having its assumptions, advantages, and limitations, and being suitable to particular noise model.
Accordingly, there is a need in the industry for developing an alternative method and system for denoising digital images, which would mitigate or avoid at least some shortcomings of the prior art.
Also, because digital images are acquired by an image sensor overlaid with a color filter array (CFA), for example a Bayer's filter, a demosaicing process is needed to remove demosaic artifacts resulting from the CFA structure of sensors, to render the digital images into a viewable format. Demosaicing process is also known as CFA interpolation or color reconstruction. Modern digital cameras can save digital images in a raw format to obtain raw images, allowing users to demosaic raw images using software, instead of using a firmware built-in the digital camera.
Usually, demosaicing methods cause several artifacts such as zipper effect and color artifact which are easily seen around edges and densely textured regions, and typically new demosaicing methods are proposed to remove or mitigate these artifacts. A survey in “Image Demosaicing: A Systematic Survey,” X. Li, B. Gunturk, L. Zhang., Proc. SPIE 6822, Visual Communications and Image Processing 2008, provides a review of demosaicing methods.
Accordingly, there is a need in the industry for developing an alternative method and system for suppressing artifacts in digital images introduced by existing demosaicing methods, which would mitigate or avoid at least the shortcomings of the prior art.